Embodiments of the present invention provide a system for converting ubiquitous language instructions to robotic process automation executable action steps and executing the action steps. A managing system receives an encrypted user input from a computing device of the user, where the user input comprises instructions entered in ubiquitous language (e.g., common vernacular, or other non-complex programming language). The user input is decrypted and an action keyword is identified from the ubiquitous language instructions. The action keyword for each instruction is compared to a conversion database to determine a set of execution steps associated with each action keyword. These execution steps are in a format that enables a robotic process automation system to perform the execution steps. The set of execution steps is then transmitted to the robotic process automation system that automatically performs the set of execution steps through a workstation or other operating station of the user.

This application discloses a decoding method, a decoding device, and a readable storage medium. The decoding method can perform a simple logic operation on the corresponding specified bits in the first bitstream, and generate the corresponding fourth bitstream accordingly to obtain information before encoding. The logic design of this decoding method is simple, which can reduce the complexity of logic circuit design and improve the reliability of decoding.

This application discloses a decoding method, a decoding device, and a readable storage medium. The decoding method can perform a simple logic operation on the corresponding specified bits in the first bitstream, and generate the corresponding fourth bitstream accordingly to obtain information before encoding. The logic design of this decoding method is simple, which can reduce the complexity of logic circuit design and improve the reliability of decoding.

This disclosure provides methods, devices, and systems for data compression. The present implementations more specifically relate to encoding techniques for compressing probability tables used for entropy coding. In some aspects, an entropy encoder may encode a probability table so that one or more contexts are represented by fewer bits than would otherwise be needed to represent the frequency of each symbol as a proportion of the total frequency of all symbols associated with such contexts. For example, if a given row of the probability table (prior to encoding) includes a number (M) of entries each having a binary value represented by a number (K) of bits, the same row of entries may be represented by fewer than M*K bits in the encoded probability table.

A microelectromechanical systems (MEMS) switching circuit and related apparatus is provided. A MEMS apparatus includes a MEMS switching circuit and a control circuit. The MEMS switching circuit includes a first number of MEMS switches, each configured to close and open based on a high driving voltage and a low driving voltage, respectively. The MEMS switching circuit includes a MEMS-based driver circuit configured to receive a second number of control signals that collectively identify a selected MEMS switch among the first number of MEMS switches. Accordingly, the MEMS-based driver circuit decodes the second number of control signals and causes the selected MEMS switch to close. By using a lesser number of control signals to control a larger number of MEMS switches, it may be possible to reduce control lines between the control circuit and the MEMS switching circuit, thus helping to reduce routing complexity and footprint of the MEMS apparatus.

Embodiments of the present invention provide a system for converting ubiquitous language instructions to robotic process automation executable action steps and executing the action steps. A managing system receives an encrypted user input from a computing device of the user, where the user input comprises instructions entered in ubiquitous language (e.g., common vernacular, or other non-complex programming language). The user input is decrypted and an action keyword is identified from the ubiquitous language instructions. The action keyword for each instruction is compared to a conversion database to determine a set of execution steps associated with each action keyword. These execution steps are in a format that enables a robotic process automation system to perform the execution steps. The set of execution steps is then transmitted to the robotic process automation system that automatically performs the set of execution steps through a workstation or other operating station of the user.

Embodiments of the present invention provide a system for converting ubiquitous language instructions to robotic process automation executable action steps and executing the action steps. A managing system receives an encrypted user input from a computing device of the user, where the user input comprises instructions entered in ubiquitous language (e.g., common vernacular, or other non-complex programming language). The user input is decrypted and an action keyword is identified from the ubiquitous language instructions. The action keyword for each instruction is compared to a conversion database to determine a set of execution steps associated with each action keyword. These execution steps are in a format that enables a robotic process automation system to perform the execution steps. The set of execution steps is then transmitted to the robotic process automation system that automatically performs the set of execution steps through a workstation or other operating station of the user.

Systems and methods evaluate simulation models and measure floating point arithmetic errors in terms of Unit in Last Place (ULP). The simulation model may include model elements that perform numerical computations using Native Floating Point (NFP) arithmetic. The model elements may be arranged to implement a procedure. A data store may include local ULP errors predetermined for the model elements. The systems and methods may retrieve the local ULP errors for the model elements included in the model, and may apply a rules-based analysis to compute an overall ULP error of the simulation model. The systems and methods may present the overall ULP computed for the model. The systems and methods may also present intermediate ULP errors determined for portions of the simulation model. Changes may be made to the model to reduce the overall ULP error.

Systems and methods evaluate simulation models and measure floating point arithmetic errors in terms of Unit in Last Place (ULP). The simulation model may include model elements that perform numerical computations using Native Floating Point (NFP) arithmetic. The model elements may be arranged to implement a procedure. A data store may include local ULP errors predetermined for the model elements. The systems and methods may retrieve the local ULP errors for the model elements included in the model, and may apply a rules-based analysis to compute an overall ULP error of the simulation model. The systems and methods may present the overall ULP computed for the model. The systems and methods may also present intermediate ULP errors determined for portions of the simulation model. Changes may be made to the model to reduce the overall ULP error.

A computer-implemented method for coding a digital signal intended to be processed by a digital computing system includes the steps of: receiving a sample of the digital signal quantized on a number N.sub.d of bits, decomposing the sample into a plurality of binary words of parameterizable bit size N.sub.p, coding the sample through a plurality of pairs of values, each pair comprising one of the binary words and an address corresponding to the position of the binary word in the sample, transmitting the pairs of values to an integration unit in order to carry out a MAC operation between the sample and a weighting coefficient.